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Open AccessArticle

An On-Demand Scalable Model for Geographic Information System (GIS) Data Processing in a Cloud GIS

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School of Computer Science, China University of Geosciences, No.388 Lumo Road, Wuhan 430074, China
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Hubei Key Laboratory of Intelligent Geo-Information Processing, China University of Geosciences, Wuhan 430074, China
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Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, No.9 Dengzhuang South Road, Beijing 100094, China
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School of Information Engineering, China University of Geosciences(Beijing), No.29 Xueyuan Road, Beijing 100083, China
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Key Laboratory of Geological Information Technology, Ministry of Natural Resources, Beijing 100037, China
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2019, 8(9), 392; https://doi.org/10.3390/ijgi8090392
Received: 25 July 2019 / Revised: 28 August 2019 / Accepted: 30 August 2019 / Published: 4 September 2019
With the rapid development of information processing technology and continuously evolving technological hardware and software, the scale of spatial data has grown exponentially. This has necessitated that stricter requirements be placed on the way data is processed. The traditional single-machine centralized data processing method is gradually being replaced by the network-based cloud geographic information system (GIS) mode. However, the information processing method of the business system in the existing spatial information network environment is difficult to expand, which limits the application of the business system. This paper proposes an on-demand and extended model for the GIS data processing procedure that considers the three-way separation of algorithm development, business processes, and the operational interface, and can implement an on-demand expansion of business processes by process modeling the business and task scheduling the workflow engine. This can expand the scope of business systems and improve the efficiency of business system construction. View Full-Text
Keywords: data processing; geological big data; service model data processing; geological big data; service model
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Zhang, J.; Xu, L.; Zhang, Y.; Liu, G.; Zhao, L.; Wang, Y. An On-Demand Scalable Model for Geographic Information System (GIS) Data Processing in a Cloud GIS. ISPRS Int. J. Geo-Inf. 2019, 8, 392.

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